{"id":"https://openalex.org/W2900296094","doi":"https://doi.org/10.3390/data4010015","title":"Machine-Learning Models for Sales Time Series Forecasting","display_name":"Machine-Learning Models for Sales Time Series Forecasting","publication_year":2019,"publication_date":"2019-01-18","ids":{"openalex":"https://openalex.org/W2900296094","doi":"https://doi.org/10.3390/data4010015","mag":"2900296094"},"language":"en","primary_location":{"id":"doi:10.3390/data4010015","is_oa":true,"landing_page_url":"https://doi.org/10.3390/data4010015","pdf_url":"https://www.mdpi.com/2306-5729/4/1/15/pdf?version=1548153423","source":{"id":"https://openalex.org/S4210226510","display_name":"Data","issn_l":"2306-5729","issn":["2306-5729"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2306-5729/4/1/15/pdf?version=1548153423","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026355556","display_name":"Bohdan M. Pavlyshenko","orcid":"https://orcid.org/0000-0001-9515-3488"},"institutions":[{"id":"https://openalex.org/I200280692","display_name":"Lviv University","ror":"https://ror.org/01s7y5e82","country_code":"UA","type":"education","lineage":["https://openalex.org/I200280692"]}],"countries":["UA"],"is_corresponding":true,"raw_author_name":"Bohdan Pavlyshenko","raw_affiliation_strings":["Ivan Franko National University of Lviv, 1, Universytetska St., 79000 Lviv, Ukraine","SoftServe, Inc., 2D Sadova St., 79021 Lviv, Ukraine"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ivan Franko National University of Lviv, 1, Universytetska St., 79000 Lviv, Ukraine","institution_ids":["https://openalex.org/I200280692"]},{"raw_affiliation_string":"SoftServe, Inc., 2D Sadova St., 79021 Lviv, Ukraine","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5026355556"],"corresponding_institution_ids":["https://openalex.org/I200280692"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":24.5413,"has_fulltext":false,"cited_by_count":231,"citation_normalized_percentile":{"value":0.99725227,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"4","issue":"1","first_page":"15","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14351","display_name":"Statistical and Computational Modeling","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.737541913986206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6996244788169861},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.677513837814331},{"id":"https://openalex.org/keywords/sales-forecasting","display_name":"Sales forecasting","score":0.6435601115226746},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6078388690948486},{"id":"https://openalex.org/keywords/predictive-analytics","display_name":"Predictive analytics","score":0.5963259339332581},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5806356072425842},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.546302080154419},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4905650019645691},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4802182614803314},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4463224411010742},{"id":"https://openalex.org/keywords/technology-forecasting","display_name":"Technology forecasting","score":0.4373113811016083},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4323224723339081},{"id":"https://openalex.org/keywords/probabilistic-forecasting","display_name":"Probabilistic forecasting","score":0.43199366331100464},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.42487940192222595},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.35532891750335693},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3187454044818878},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.09347555041313171},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09293505549430847}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.737541913986206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6996244788169861},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.677513837814331},{"id":"https://openalex.org/C2984642479","wikidata":"https://www.wikidata.org/wiki/Q7404320","display_name":"Sales forecasting","level":2,"score":0.6435601115226746},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6078388690948486},{"id":"https://openalex.org/C83209312","wikidata":"https://www.wikidata.org/wiki/Q1053367","display_name":"Predictive analytics","level":2,"score":0.5963259339332581},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5806356072425842},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.546302080154419},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4905650019645691},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4802182614803314},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4463224411010742},{"id":"https://openalex.org/C161657586","wikidata":"https://www.wikidata.org/wiki/Q1203326","display_name":"Technology forecasting","level":2,"score":0.4373113811016083},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4323224723339081},{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.43199366331100464},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.42487940192222595},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.35532891750335693},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3187454044818878},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.09347555041313171},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09293505549430847},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/data4010015","is_oa":true,"landing_page_url":"https://doi.org/10.3390/data4010015","pdf_url":"https://www.mdpi.com/2306-5729/4/1/15/pdf?version=1548153423","source":{"id":"https://openalex.org/S4210226510","display_name":"Data","issn_l":"2306-5729","issn":["2306-5729"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:gam:jdataj:v:4:y:2019:i:1:p:15-:d:198898","is_oa":false,"landing_page_url":"https://www.mdpi.com/2306-5729/4/1/15/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:1f4d23c64349461b97b23172ce827e3e","is_oa":true,"landing_page_url":"https://doaj.org/article/1f4d23c64349461b97b23172ce827e3e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data, Vol 4, Iss 1, p 15 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2306-5729/4/1/15/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/data4010015","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/data4010015","is_oa":true,"landing_page_url":"https://doi.org/10.3390/data4010015","pdf_url":"https://www.mdpi.com/2306-5729/4/1/15/pdf?version=1548153423","source":{"id":"https://openalex.org/S4210226510","display_name":"Data","issn_l":"2306-5729","issn":["2306-5729"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2900296094.pdf","grobid_xml":"https://content.openalex.org/works/W2900296094.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1524104189","https://openalex.org/W1534477342","https://openalex.org/W1678356000","https://openalex.org/W1909207154","https://openalex.org/W2014928429","https://openalex.org/W2070493638","https://openalex.org/W2092595282","https://openalex.org/W2105119576","https://openalex.org/W2155806188","https://openalex.org/W2170378253","https://openalex.org/W2170391700","https://openalex.org/W2295598076","https://openalex.org/W2487770199","https://openalex.org/W2489540272","https://openalex.org/W2561590197","https://openalex.org/W2602516395","https://openalex.org/W2760894977","https://openalex.org/W2766801343","https://openalex.org/W2789758093","https://openalex.org/W2790601685","https://openalex.org/W2798056406","https://openalex.org/W2887451828","https://openalex.org/W2895303784","https://openalex.org/W2901999103","https://openalex.org/W2903132559","https://openalex.org/W2911964244","https://openalex.org/W2964170972","https://openalex.org/W3125627124","https://openalex.org/W4206262190","https://openalex.org/W4247629194","https://openalex.org/W6735918670","https://openalex.org/W6740952796","https://openalex.org/W6756558598"],"related_works":["https://openalex.org/W4401228152","https://openalex.org/W3108868229","https://openalex.org/W4205686051","https://openalex.org/W3189884647","https://openalex.org/W4313451520","https://openalex.org/W4206275624","https://openalex.org/W3134571208","https://openalex.org/W3203664106","https://openalex.org/W4251864566","https://openalex.org/W2582097002"],"abstract_inverted_index":{"In":[0],"this":[1,18],"paper,":[2],"we":[3,97],"study":[4],"the":[5,67,100],"usage":[6],"of":[7,17,28,37,58,84,102],"machine-learning":[8,38],"models":[9,86,104],"for":[10,32,61,80,105],"sales":[11,33,50,63,106],"predictive":[12,103],"analytics.":[13],"The":[14,35,90],"main":[15,23],"goal":[16],"paper":[19],"is":[20,54,75],"to":[21,48],"consider":[22],"approaches":[24],"and":[25],"case":[26,68],"studies":[27],"using":[29,94],"machine":[30],"learning":[31],"forecasting.":[34,109],"effect":[36,44],"generalization":[39],"has":[40,87],"been":[41,88],"considered.":[42],"This":[43],"can":[45,98],"be":[46],"used":[47],"make":[49],"predictions":[51],"when":[52,69],"there":[53],"a":[55,70],"small":[56],"amount":[57],"historical":[59],"data":[60],"specific":[62],"time":[64,107],"series":[65,108],"in":[66],"new":[71],"product":[72],"or":[73],"store":[74],"launched.":[76],"A":[77],"stacking":[78,95],"approach":[79],"building":[81],"regression":[82],"ensemble":[83],"single":[85],"studied.":[89],"results":[91],"show":[92],"that":[93],"techniques,":[96],"improve":[99],"performance":[101]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":41},{"year":2023,"cited_by_count":41},{"year":2022,"cited_by_count":43},{"year":2021,"cited_by_count":45},{"year":2020,"cited_by_count":26},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-26T08:31:28.666265","created_date":"2025-10-10T00:00:00"}